JP7464880B2 - Biological information analysis system, non-transitory storage medium, and biological information analysis method - Google Patents

Description

The present invention relates to a biometric information analysis system, a non-transitory storage medium, and a biometric information analysis method.

In medical and nursing care settings, a system has been proposed that uses sensors to monitor a patient's biological information during daily activities 24 hours a day and provide appropriate treatment (see, for example, Non-Patent Document 1). Such a system includes, for example, a sensor terminal that acquires biological information data, a relay terminal that acquires the biological information data from the sensor terminal and relays it to another device, and an external terminal that performs analysis based on the biological information data. In such a system, in order to reduce the traffic load in the network between the relay terminal and the external terminal, downsampling is performed on the biological information data at the relay terminal. Downsampling can be done by periodically thinning out data or periodically calculating statistics (for example, the average value) of data over a certain period of time.

There are also several types of technologies for transmitting the biometric data to be downsampled from the sensor terminal to the relay terminal. For example, there is a technology that transmits the data from the sensor terminal to the relay terminal in real time using a wireless module. For example, there is also a technology that accumulates the biometric data in the built-in memory of the sensor terminal and later transmits it to the relay terminal at a predetermined timing (for example, see Non-Patent Document 2).

"Rehabilitation support using wearable material hitoe," NTT Technical Journal "Development of a low-power, small-sized wearable sensor capable of measuring electrocardiogram, acceleration, temperature and humidity for smart healthcare" <URL: https://www.ntt.co.jp/news2019/1911/191108a.html>

When data is transferred from a sensor terminal to a relay device, communication may fail due to noise or interference during wireless communication (e.g., Bluetooth Low Energy: BLE). When the data is subsequently reconnected and transmission is resumed, processing using the transmitted data may not be performed appropriately. For example, it is difficult to determine whether the data arriving at the relay terminal after the transmission is resumed should be treated as a single block of data with the data transmitted before the restart, or should be treated as a separate block of data from the data transmitted before the restart, and the data may be mishandled. If the data is mishandled, there is a risk of the accuracy of the data decreasing. Examples of data that should be treated as a single block of data include, for example, biometric data of the same user, and data used to produce the same statistical value. Examples of data that should be treated as a separate block of data from the data transmitted before the restart include, for example, biometric data of another user, biometric data newly transmitted after communication has been normally terminated, and data used to produce different statistical values.
In addition, in order to prevent mishandling, in the event of a communication failure, some data that had been transmitted before the transmission was resumed would not be used in the calculation of statistics. However, such processing could result in some data being lost, which could reduce the accuracy of subsequent analysis.

In view of the above circumstances, the present invention aims to provide technology that makes it possible to prevent a decrease in data accuracy and loss of data even if a failure occurs in data communication.

One aspect of the present invention is a bioinformation analysis system comprising a data receiving unit that receives time series data of bioinformation from a sensor terminal having a biosensor that acquires bioinformation, a memory unit that stores the received time series data, a first representative value acquisition unit that acquires a first representative value based on data of a predetermined period from the received time series data, and a second representative value acquisition unit that acquires a second representative value based on a plurality of the first representative values that are consecutive on the time axis, wherein when an error occurs in communication between the data receiving unit and the sensor terminal, and a predetermined condition is satisfied, the first representative value acquisition unit acquires the first representative value using pre-error time series data that was transmitted before the error occurred and stored in the memory unit, and post-error time series data transmitted from the sensor terminal after the error occurred.

One aspect of the present invention is a non-transitory storage medium storing a program for causing a computer to function as the above-mentioned bioinformation analysis system.

One aspect of the present invention is a bioinformation analysis method comprising a data receiving step of receiving time series data of the bioinformation from a sensor terminal having a biosensor that acquires the bioinformation, a storage step of storing the received time series data, a first representative value acquisition step of acquiring a first representative value based on data of a predetermined period from the received time series data, and a second representative value acquisition step of acquiring a second representative value based on a plurality of the first representative values that are consecutive on the time axis, wherein in the first representative value acquisition step, if an error occurs in communication between the data receiving unit and the sensor terminal, and if a predetermined condition is satisfied, the first representative value is acquired using pre-error time series data that was transmitted before the error occurred and stored in the storage unit, and post-error time series data that was transmitted from the sensor terminal after the error occurred.

The present invention makes it possible to prevent a decrease in data accuracy and loss of data even if a failure occurs in data communication.

FIG. 1 is a block diagram illustrating the functions of a biological information analysis apparatus according to a first embodiment of the present invention. FIG. 2 is a block diagram showing a hardware configuration of the biological information analysis apparatus according to the first embodiment. FIG. 3 is a flowchart illustrating the biological information analyzing method according to the first embodiment. FIG. 4 is a diagram illustrating the process of calculating the representative value according to the first embodiment. FIG. 5 is a diagram showing a configuration of a biological information analyzing system according to the first embodiment. FIG. 6 is a block diagram showing a configuration of the biological information analyzing system according to the first embodiment. FIG. 7 is a sequence diagram illustrating the operation of the biological information analyzing system according to the first embodiment. FIG. 8 is a block diagram illustrating the functions of the biological information analysis apparatus according to the second embodiment. FIG. 9 is a diagram illustrating the adjustment process according to the second embodiment. FIG. 10 is a diagram for explaining the final representative value at the data end according to the second embodiment. FIG. 11 is a sequence diagram illustrating the operation of the biological information analyzing system according to the second embodiment. FIG. 12 is a diagram illustrating the effect of the biological information analysis apparatus according to the second embodiment. FIG. 13 is a block diagram illustrating the functions of a biological information analysis apparatus according to the third embodiment of the present invention. FIG. 14 is a diagram illustrating the process of calculating the representative value according to the third embodiment. FIG. 15 is a block diagram showing a configuration of a biological information analyzing system according to the third embodiment. FIG. 16 is a sequence diagram illustrating the operation of the biological information analyzing system according to the third embodiment. FIG. 17 is a block diagram illustrating the functions of a biological information analysis apparatus according to the fourth embodiment of the present invention. FIG. 18 is a diagram illustrating the process of calculating the representative value according to the fourth embodiment. FIG. 19 is a block diagram showing a configuration of a biological information analyzing system according to the fourth embodiment. FIG. 20 is a sequence diagram illustrating the operation of the biological information analyzing system according to the fourth embodiment. FIG. 21 is a block diagram illustrating the functions of a biological information analysis apparatus according to the fifth embodiment of the present invention. FIG. 22 is a diagram illustrating the process of calculating the representative value according to the fifth embodiment. FIG. 23 is a block diagram showing a configuration of a biological information analyzing system according to the fifth embodiment. As shown in FIG. FIG. 24 is a sequence diagram illustrating the operation of the biological information analyzing system according to the fifth embodiment. FIG. 25 is a block diagram illustrating the functions of a biological information analyzer according to a modification of the fifth and sixth embodiments of the present invention. FIG. 26 is a sequence diagram illustrating the operation of the biological information analyzing system according to the sixth embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will now be described in detail with reference to FIGS.
[First embodiment]
First, an outline of the configuration of a biological information analysis device 1 according to a first embodiment of the present invention will be described.
FIG. 1 is a block diagram showing the functional configuration of a biological information analysis device 1.

[Functional blocks of the bioinformation analyzer]
The biological information analysis device 1 includes a sensor data acquisition unit 10 , a control unit 11 , a time acquisition unit 12 , a storage unit 13 , a presentation unit 14 , and a transmission/reception unit 15 .

The sensor data acquisition unit 10 acquires biometric information of the user measured by a sensor 105 (described later) worn by the user. More specifically, for example, when a heart rate monitor is worn by the user as the sensor 105, the sensor data acquisition unit 10 calculates the heart rate from an electrocardiogram waveform based on the cardiac potential measured by the heart rate monitor. In addition, when an acceleration sensor is worn by the user as the sensor (biosensor) 105, the sensor data acquisition unit 10 converts an analog acceleration signal measured by the acceleration sensor into a digital signal at a predetermined sampling rate.

The sensor data acquisition unit 10 outputs time series data in which the heart rate and digital acceleration signal are associated with the measurement time at which the acceleration signal was acquired by the sensor 105. In this example, the heart rate and acceleration data are bioinformation. The time series data of the bioinformation measured by the sensor data acquisition unit 10 is stored in the memory unit 13, which will be described later.

The control unit 11 includes a first representative value acquisition unit 110 and a second representative value acquisition unit 111. The control unit 11 acquires a statistical representative value of the time series data of the user's biometric information stored in the memory unit 13. In this embodiment, the statistical representative value of the time series data of the user's biometric information is acquired by calculating it through an arithmetic operation. In order to acquire a statistical representative value of the time series data of the user's biometric information, in addition to calculation, processing using a lookup table, for example, may be used. In this embodiment, the control unit 11 calculates the representative value of the biometric information in two stages. The control unit 11 may calculate, for example, the average value or ratio of the biometric information for each certain period as the representative value of the biometric information.

The first representative value acquisition unit 110 calculates a first representative value (hereinafter referred to as an "intermediate representative value"), which is an intermediate representative value of the biometric information, for each set period from the time series data of the user's biometric information. The calculated intermediate representative value is stored in the memory unit 13. More specifically, the first representative value acquisition unit 110 calculates an intermediate representative value indicating the average value every 60 seconds, for example, in the time series data of the biometric information acquired by the sensor data acquisition unit 10.

The second representative value acquisition unit 111 calculates a second representative value (hereinafter referred to as the "final representative value"), which is the final representative value of the time series data of the biological information, based on one intermediate representative value or multiple consecutive intermediate representative values. The calculated final representative value is stored in the memory unit 13.

More specifically, the second representative value acquisition unit 111 calculates one final representative value using, for example, five consecutive intermediate representative values. For example, based on five consecutive intermediate representative values calculated at 60-second intervals, the second representative value acquisition unit 111 calculates a representative value for a five-minute period as the final representative value. Note that the number of consecutive intermediate representative values used by the second representative value acquisition unit 111 when calculating the final representative value can be set arbitrarily.

The time acquisition unit 12 acquires a reference time used in the bioinformation analysis device 1. The time acquisition unit 12 may acquire the reference time from, for example, a clock 107 provided in the bioinformation analysis device 1, or may acquire the time information from a time server (not shown). The time information acquired by the time acquisition unit 12 is used when the sensor data acquisition unit 10 samples the bioinformation, and for calculating the period when the first representative value acquisition unit 110 calculates the intermediate representative value.

The memory unit 13 stores time series data of the user's biometric information measured by the sensor data acquisition unit 10. The memory unit 13 also stores an intermediate representative value calculated for each set period by the first representative value acquisition unit 110. The memory unit 13 also stores a final representative value calculated by the second representative value acquisition unit 111.

The presentation unit 14 presents the representative value calculated by the control unit 11. More specifically, the presentation unit 14 displays the final representative value of the biometric information on the display device 109 described below. The presentation unit 14 also generates and presents information to assist the user based on the final representative value. The presentation unit 14 may output the information to assist the user to an operating device (not shown) realized by the display device 109, an audio output device, a light source, an actuator, a heating device, or the like.

The transmission/reception unit 15 receives sensor data indicating biometric information measured by the sensor 105 described below. The transmission/reception unit 15 can also transmit the final representative value of the biometric information by the control unit 11 to the outside via the communication network.

[Hardware configuration of the biological information analysis device]
Next, an example of the hardware configuration of the biological information analyzer 1 having the above-mentioned functions will be described with reference to the block diagram of FIG.

2, the bioinformation analysis device 1 can be realized by, for example, a computer including a CPU 102, a main memory device 103, a communication interface 104, an auxiliary memory device 106, a clock 107, and an input/output device 108, which are connected via a bus 101, and a program that controls these hardware resources. An external sensor 105 and a display device 109 are each connected to the bioinformation analysis device 1 via the bus 101.

The main memory 103 stores in advance programs that the CPU 102 uses to perform various controls and calculations. The CPU 102 and the main memory 103 realize the various functions of the bioinformation analysis device 1, including the control unit 11 shown in FIG. 1.

The communication interface 104 is an interface circuit for communicating with various external electronic devices via the communication network NW.

The communication interface 104 may be, for example, an arithmetic interface and an antenna that are compatible with wireless data communication standards such as LTE (Long Term Evolution), 3G, wireless LAN (Local Area Network), and Bluetooth (registered trademark). The communication interface 104 realizes the transceiver 15 described in FIG. 1.

The sensor 105 is realized by, for example, a sensor such as a heart rate monitor, an electrocardiogram, or an acceleration sensor. The sensor 105 is worn by the user for a preset measurement period and measures biometric information such as the user's heart rate and acceleration.

The auxiliary storage device 106 is composed of a readable/writable storage medium and a drive for reading and writing various information such as programs and data from the storage medium. The auxiliary storage device 106 can use semiconductor memory such as a hard disk or flash memory as the storage medium.

The auxiliary storage device 106 has a storage area for storing time series data of the bioinformation measured by the sensor 105, and a program storage area for storing a program for the bioinformation analysis device 1 to perform an analysis process of the bioinformation. The auxiliary storage device 106 realizes the memory unit 13 described in FIG. 1. Furthermore, it may have, for example, a backup area for backing up the above-mentioned data and programs.

The clock 107 is composed of an internal clock built into the computer and keeps time. The time information obtained by the clock 107 is used for sampling the biometric information and calculating the representative value. The time information obtained by the clock 107 is obtained by the time acquisition unit 12 described in FIG. 1.

The input/output device 108 is composed of I/O terminals that input signals from external devices such as the sensor 105 and the display device 109, and output signals to external devices.

The display device 109 functions as the presentation unit 14 of the bioinformation analysis device 1. The display device 109 is realized by a liquid crystal display or the like. The display device 109 also constitutes an operating device that outputs user support information generated based on the final representative value of the bioinformation.

[Biometric information analysis method]
Next, the operation of the biological information analyzer 1 having the above-mentioned configuration will be described with reference to the flowchart of Fig. 3. First, the following process is executed in a state where the sensor 105 is attached to the user.

The sensor data acquisition unit 10 acquires biometric information measured by the sensor 105 worn by the user (step S1). More specifically, the sensor data acquisition unit 10 acquires the biometric information and outputs time-series data in which the biometric information and the measurement time are associated with each other. Next, the time-series data of the biometric information is stored in the storage unit 13 (step S2).

Next, the first representative value acquisition unit 110 calculates an intermediate representative value of the time series data of the biological information measured in step S1 (step S3). More specifically, the first representative value acquisition unit 110 calculates the average value of the time series data of the biological information for each set period, for example, every 60 seconds.

Then, after a predetermined time has elapsed, the second representative value acquisition unit 111 calculates a final representative value of the time series data of the biological information based on the intermediate representative value calculated in step S3 (step S4). More specifically, the second representative value acquisition unit 111 calculates a representative value of a plurality of consecutive intermediate representative values set in advance as the final representative value. For example, the second representative value acquisition unit 111 may calculate an average value of five consecutive intermediate representative values after these intermediate representative values are calculated in step S3. Then, the control unit 11 outputs the final representative value calculated in step S4 (step S5). Note that the control unit 11 may output the intermediate representative value calculated in step S3 together with the final representative value.

Figure 4 is a diagram for explaining an example of the representative value calculation process by the control unit 11. The top row (a) in Figure 4 shows the data string of the biometric information acquired by the sensor data acquisition unit 10 along with the elapsed time. The middle row (b) shows the string of intermediate representative values and the measurement period of the biometric data that was the basis for calculating each intermediate representative value (hereinafter sometimes referred to as the "calculation period"). The bottom row (c) shows the string of final representative values and the period of their calculation range.

Here, the intermediate representative value A _i represents the i-th calculated intermediate representative value and is expressed in the form of a matrix. If the sum of the measurement values of the biological information in an arbitrary period is S _i and the number of the measurement values is N _i , the intermediate representative value A _i is expressed by the following formula (1).

In the above formula (1), a _t is the measurement value of the biological information at the measurement time t, and t1 and t2 are the start and end times of the period set for calculating the intermediate representative value, respectively. In addition, in the above formula (1), the length of the calculation period is set to 60 seconds, and the biological information a _t during that period is sampled at a 1/f cycle. In this embodiment, an example is given in which the calculation period slides by one, that is, by 60 seconds, every time i increases by one.

The final representative value B _i is expressed by the following equation (2).

Each function of the bioinformation analysis device 1 described above may not only be provided on a single computer, but may also be distributed across multiple computers that are communicatively connected to each other via a communication network.

[Biometric information analysis system]
Next, a biological information analysis system that specifically configures the biological information analysis device 1 according to the present invention will be described with reference to FIGS.
5, the bioinformation analysis system includes a sensor terminal 200 worn by a user 500, a relay terminal 300, and an external terminal 400. All or any of the sensor terminal 200, the relay terminal 300, and the external terminal 400 include the functions of the bioinformation analysis device 1, such as the control unit 11 described in Fig. 1. In the following, a case will be described in which the relay terminal 300 includes the control unit 11 described in Fig. 1.

[Sensor terminal functional block]
The sensor terminal 200 includes a sensor (biometric sensor) 201, a sensor data acquisition unit 202, a data storage unit 203, and a data transmission unit 204. The sensor terminal 200 is placed, for example, on the trunk of the body of the user 500 and measures biological information over a plurality of time periods. The sensor terminal 200 transmits the measured biological information of the user 500 to the relay terminal 300 via the communication network NW.

The sensor 201 is realized by a heart rate monitor, an acceleration sensor, or the like. The three axes of the acceleration sensor provided in the sensor 201 are arranged in parallel, for example, as shown in Fig. 5, with the X axis being the left-right direction of the body, the Y axis being the front-back direction of the body, and the Z axis being the up-down direction of the body. The sensor 201 corresponds to the sensor 105 described in Fig. 2.

The sensor data acquisition unit 202 acquires bioinformation measured by the sensor 201. More specifically, the sensor data acquisition unit 202 removes noise from the acquired bioinformation as necessary, performs sampling processing, and obtains time series data of the digital signal bioinformation. The sensor data acquisition unit 202 corresponds to the sensor data acquisition unit 10 described in FIG. 1.

The data storage unit 203 stores time series data of the biometric information detected by the sensor 201 and the biometric information in the form of a digital signal obtained by processing by the sensor data acquisition unit 202. The data storage unit 203 corresponds to the storage unit 13 (Figure 1).

The data transmission unit 204 transmits the time series data of the biological information stored in the data storage unit 203 to the relay terminal 300 via the communication network NW. The data transmission unit 204 includes a communication circuit for performing wireless communication corresponding to wireless data communication standards such as LTE, 3G, wireless LAN, and Bluetooth (registered trademark). The data transmission unit 204 corresponds to the transmission/reception unit 15 (Figure 1).

[Function block of relay terminal]
The relay terminal 300 includes a data receiving unit 301, a data storage unit 302, a time acquiring unit 303, a control unit 304, and a data transmitting unit 307. The relay terminal 300 gradually obtains a statistical representative value from the time series data of the biometric information of the user 500 received from the sensor terminal 200. Furthermore, the relay terminal 300 transmits the calculated representative value to the external terminal 400.

The relay terminal 300 may be realized by a smartphone, tablet, laptop, etc.

The data receiving unit 301 receives time series data of biometric information from the sensor terminal 200 via the communication network NW. The data receiving unit 301 corresponds to the transmitting/receiving unit 15 (Figure 1).

The data storage unit 302 stores the biometric information of the user 500 received by the data receiving unit 301 and representative values of the biometric information acquired by the control unit 304. The data storage unit 302 corresponds to the storage unit 13 (Figure 1).

The time acquisition unit 303 acquires time information from the built-in clock (clock 107) to be used in the analysis process of the biometric information by the control unit 304. The time acquisition unit 303 corresponds to the time acquisition unit 12 described in FIG. 1.

The control unit 304 includes a first representative value acquisition unit 305 and a second representative value acquisition unit 306 .
The control unit 304 gradually obtains a statistical representative value, such as an average value, of the time-series data of the biometric information of the user 500 received by the data receiving unit 301. The control unit 304 corresponds to the control unit 11 described in FIG.

The first representative value acquisition unit 305 calculates an intermediate representative value from the time-series data of the biological information of the user 500 for a set period, for example, every 60 seconds. The calculated intermediate representative value is stored in the data storage unit 302.
The second representative value acquisition unit 306 calculates a final representative value from a plurality of successive intermediate representative values.
The first representative value acquiring section 305 and the second representative value acquiring section 306 correspond to the first representative value acquiring section 110 and the second representative value acquiring section 111 described in FIG. 1, respectively.

The data transmission unit 307 transmits the final representative value calculated by the second representative value acquisition unit 306 to the external terminal 400 via the communication network NW. The data transmission unit 307 corresponds to the transmission/reception unit 15 (Figure 1). The data transmission unit 307 may transmit the intermediate representative value together with the final representative value.

[External terminal function block]
The external terminal 400 includes a data receiving unit 401, a data storage unit 402, a presentation processing unit 403, and a presentation unit 404. The external terminal 400 presents a final representative value of the biometric information of the user 500 received from the relay terminal 300 via the communication network NW. The external terminal 400 presents support information to the user 500 that is generated based on the calculated final representative value.

The external terminal 400, like the relay terminal 300, is realized by a smartphone, tablet, notebook computer, etc. The external terminal 400 is equipped with a display device that displays the received final representative value, and an operating device (not shown) that outputs information to support the user 500 that is generated based on the calculated final representative value. Examples of the operating device equipped in the external terminal 400 include a display device, an audio output device, a light source, an actuator, and a heating device.

For example, a speaker or a musical instrument may be used as the audio output device. An LED (Light Emitting Diode) or a light bulb may be used as the light source. A vibrator, a robot arm, or an electric treatment device may be used as the actuator. A heater or a Peltier element may be used as the heating device.

The data receiving unit 401 receives the final representative value of the biometric information from the relay terminal 300 via the communication network NW. The data receiving unit 401 corresponds to the transmitting/receiving unit 15 (Figure 1).

The data storage unit 402 stores the final representative value of the biometric information received by the data receiving unit 401. The data storage unit 402 corresponds to the storage unit 13 (Figure 1).

The presentation processing unit 403 generates support information for the user 500 based on the received final representative value. The presentation processing unit 403 corresponds to the presentation unit 14 described in FIG. 1.

The presentation unit 404 presents support information to the user 500 based on the presentation of the final representative value and instructions from the presentation processing unit 403. More specifically, the final representative value and support information may be displayed as text information or graphs on a display device provided in the external terminal 400, or the support information may be output as an alert sound from a speaker (not shown) provided in the external terminal 400. In addition, the presentation unit 404 can present the support information by a method that can be recognized by the user 500, such as vibration or light. The presentation unit 404 corresponds to the presentation unit 14 described in FIG. 1.

In this way, the bioinformation analysis system of the present invention has a configuration in which the functions of the bioinformation analysis device 1 are distributed to the sensor terminal 200, the relay terminal 300, and the external terminal 400, and the processing related to calculating the representative value from the measurement of the bioinformation of the user 500 and presenting the final representative value is performed in a distributed manner.

[Operation sequence of the biological information analysis system]
Next, the operation of the biological information analysis system having the above-mentioned configuration will be described with reference to the sequence diagram of Fig. 7. In the following, a representative value of the heart rate of the user 500 will be calculated as an example of biological information.

7, first, the sensor terminal 200 worn by the user 500 measures the heart rate of the user 500 (step S100). More specifically, the sensor 201 consisting of a heart rate monitor measures the cardiac potential of the user 500. The sensor data acquisition unit 202 acquires the heart rate of the user 500 from an electrocardiogram waveform based on the cardiac potential.

Next, the sensor terminal 200 transmits the time series data of the heart rate of the user 500 to the relay terminal 300 via the communication network NW (step S101). When the relay terminal 300 receives the time series data of the heart rate from the sensor terminal 200, the relay terminal 300 stores the received time series data in the data storage unit 302 (step S102). The relay terminal 300 calculates an intermediate representative value for each set period from the received time series data (step S103). More specifically, the first representative value acquisition unit 305 calculates the intermediate representative value _Ai for each 60 seconds using the above-mentioned formula (2).

Next, after a predetermined time has elapsed, the second representative value acquisition unit 306 calculates a final representative value from the successive intermediate representative values (step S104). More specifically, the second representative value acquisition unit 306 calculates a final representative value B _i using the five successive intermediate representative values by using the above-mentioned formula (2).

In this way, by using the intermediate representative value when calculating the representative value of the time series data of the acquired biometric information, for example, the number of data items, which was 300, can be reduced to 10 intermediate representative values as matrix elements, and then the final representative value can be calculated. In addition, since it is possible to repeatedly calculate the final representative value B _i at a stage prior to data transfer, it is possible to obtain an effect equivalent to downsampling the data after multiplying it by a moving average and at regular intervals (every 60 seconds in this embodiment). Therefore, it is possible to obtain an effect of reducing the amount of data to be transferred.

Returning to FIG. 7, thereafter, the relay terminal 300 transmits the final representative value of the time series data of the heart rate of the user 500 to the external terminal 400 via the communication network NW (step S105). Upon receiving the final representative value, the external terminal 400 executes a presentation process (step S106). That is, the external terminal 400 causes the final representative value to be displayed on a display device. The external terminal 400 also generates support information for the user 500 based on the final representative value, and causes the support information to be displayed on a display device or the like.

As described above, the bioinformation analysis device 1 according to the first embodiment calculates an intermediate representative value from the time-series data of the bioinformation for each set period, and calculates a final representative value based on a series of intermediate representative values. This makes it possible to simultaneously reduce and summarize the measured bioinformation.

[Second embodiment]
Next, a second embodiment of the present invention will be described. In the following description, the same components as those in the first embodiment are given the same reference numerals, and the description thereof will be omitted.

In the first embodiment, a case has been described in which the second representative value acquisition unit 111 calculates the final representative value based on a preset number of intermediate representative values. In contrast, in the second embodiment, the control unit 11A further includes an adjustment unit 112. The adjustment unit 112 varies the number of intermediate representative values used by the second representative value acquisition unit 111 to calculate the final representative value based on the number of intermediate representative values that can be secured in the past and future. The following mainly describes the configuration that differs from the first embodiment.

8, the bioinformation analysis device 1A includes a control unit 11A. The control unit 11A includes a first representative value acquisition unit 110, a second representative value acquisition unit 111, and an adjustment unit 112. Other functional configurations of the bioinformation analysis device 1A are similar to those of the first embodiment.

The adjustment unit 112 determines the number of intermediate representative values that the second representative value acquisition unit 111 uses to calculate the final representative value, based on the number of intermediate representative values that have already been calculated. More specifically, the adjustment unit 112 monitors whether there are a sufficient number of intermediate representative values for calculating the final representative value, every time the second representative value acquisition unit 111 calculates a final representative value. For example, the adjustment unit 112 counts five consecutive intermediate representative values that are required when the second representative value acquisition unit 111 calculates the final representative value B _i using the above-mentioned formula (2).

9, five consecutive intermediate representative values A _i are required for the second representative value acquisition unit 111 to calculate the final representative value B _i shown in the lower part (c). When the second representative value acquisition unit 111 calculates the final representative value B _i in response to settings or an external signal, for example, at a time point 120 seconds after the start of measurement of the biological information, five intermediate representative values A _i are required, but only one is calculated.

In this case, the adjustment unit 112 adjusts the number of intermediate representative values _Ai required for the second representative value acquisition unit 111 to calculate the final representative value. The adjustment unit 112 adopts the smaller of the number of intermediate representative values Ai already calculated at the time when the second representative value acquisition unit ₁₁₁ calculates the final representative value, or the number of intermediate representative values _Ai calculated after that time.

In other words, when the second representative value acquisition unit 111 calculates the final representative value B _i at 120 seconds from the start of measurement of the biological information, since only one intermediate representative value A _i has already been calculated, only one intermediate representative value A _i to be calculated in the future is used, and the final representative value B _i is calculated based on a total of three intermediate representative values A _i , including the one intermediate representative value A _i at 120 seconds (lower part (c'') of Figure 9).

To explain another example, when the second representative value acquisition unit 111 calculates the final representative value B _i at, for example, 60 seconds after the start of measurement of the biological information, the number of intermediate representative values A _i already calculated at the 60 second point is 0. Therefore, the adjustment unit 112 also adopts 0 as the number of intermediate representative values A _i to be calculated in the future. In this case, the second representative value acquisition unit 111 treats the intermediate representative value A _i at the 60 second point as the final representative value B _i as it is (lower part (c') of FIG. 9 ).

Also, as shown in Figure 10, at the end of the data, the measurement value of the biometric information itself may be used complementary as the final representative value (lower row (c0) of Figure 9).

[Operation sequence of the biological information analysis system]
Next, the operation of the bioinformation analysis device 1A according to this embodiment when the functions are realized by a bioinformation analysis system including the sensor terminal 200, relay terminal 300, and external terminal 400 described in Fig. 6 will be described with reference to the sequence diagram shown in Fig. 11. Note that the functional blocks of the sensor terminal 200, relay terminal 300, and external terminal 400 are similar to those described in Fig. 6. Also, it is assumed that the relay terminal 300 includes an adjustment unit 112.

First, the sensor terminal 200 is worn by the user 500, and measures, for example, the heart rate as biometric information of the user 500 (step S200). More specifically, the sensor terminal 200 detects the cardiac potential of the user 500 with a heart rate meter (sensor 201). The sensor data acquisition unit 202 acquires the cardiac potential from the sensor 201, and calculates the heart rate from an electrocardiogram waveform based on the cardiac potential. The acquired cardiac potential and heart rate are stored in the data storage unit 203.

Next, the sensor terminal 200 transmits the measured heart rate to the relay terminal 300 via the communication network NW (step S201). More specifically, the data transmission unit 204 reads out the time series data of the heart rate from the data storage unit 203 and transmits it to the relay terminal 300 via the communication network NW.

When the relay terminal 300 receives the time series data of the heart rate of the user 500 from the sensor terminal 200, the relay terminal 300 stores the received time series data in the data storage unit 302 (step S103). The relay terminal 300 calculates an intermediate representative value of the time series data of the heart rate from the received time series data in the first representative value acquisition unit 305 for a set period, for example, every 60 seconds (step S202). The calculated intermediate representative value is stored in the data storage unit 302.

Next, the adjustment unit 112 monitors the number of intermediate representative values calculated by the first representative value acquisition unit 305 (step S203). After that, for example, in response to an external signal or setting, at the time when the second representative value acquisition unit 306 calculates the final representative value, the adjustment unit 112 determines the number of intermediate representative values required to calculate the final representative value based on the number of intermediate representative values already calculated (step S204).

Then, the second representative value acquisition unit 306 calculates a final representative value based on the successive intermediate representative values according to the number of intermediate representative values determined by the adjustment unit 112 (step S205). Next, the calculated final representative value is transmitted from the relay terminal 300 to the external terminal 400 (step S206).

The external terminal 400 then receives the final representative value. The external terminal 400 performs a presentation process based on the final representative value (step S207), displays the final representative value on a display device, and generates and outputs support information for the user 500.

[Advantages of the second embodiment]
Next, the effect of the biological information analysis device 1A according to this embodiment will be described with reference to Fig. 12. In Fig. 12, the horizontal axis indicates measurement time (seconds) and the vertical axis indicates heart rate (bpm). The gray line in Fig. 12 indicates the measured heart rate, and the circle and square dots indicate the final representative value. The final representative value at measurement time 0 seconds uses the measured heart rate value as is (square dot).

The two circular points indicating the final representative values of the heart rate at the measurement times of 60 seconds and 120 seconds thereafter indicate the final representative values calculated using the number of intermediate representative values determined by the adjustment unit 112. Furthermore, the circular points from the measurement time of 180 seconds onwards indicate the final representative values calculated using five intermediate representative values without adjustment of the number of intermediate representative values by the adjustment unit 112.

As shown in Figure 12, the measured heart rate values (gray line) fluctuate up and down, but the final representative value, which fluctuates approximately in the middle of the measured values, is appropriate as a downsampled moving average.

As described above, according to the second embodiment of the biometric analysis device 1A, the adjustment unit 112 determines the number of intermediate representative values to be used when the second representative value acquisition unit 111 calculates the final representative value based on the number of intermediate representative values that have already been calculated, so that data near the start and end of biometric measurement can be effectively utilized to more precisely grasp the behavior of the user's biometric information.

In the second embodiment described above, the control unit 11A is described as being equipped with an adjustment unit 112, but the adjustment unit 112 may be provided outside the control unit 11A in the bio-information analysis device 1A.

[Third embodiment]
Next, a third embodiment of the present invention will be described. In the following description, the same components as those in the first and second embodiments are denoted by the same reference numerals, and the description thereof will be omitted.

In the third embodiment, the calculation process of the intermediate representative value is different from that in the first and second embodiments. In the third embodiment, the calculation process of the intermediate representative value is performed assuming a case where a communication failure (error) occurs between the sensor terminal 200 and the relay terminal 300B. The configuration of the third embodiment will be described below.
13, the bioinformation analyzer 1B includes a control unit 11B and a temporary storage unit 131. The control unit 11B includes a first representative value acquisition unit 110, a second representative value acquisition unit 111, and an error processing unit 114. Other functional configurations of the bioinformation analyzer 1B are similar to those of the first embodiment.

The temporary storage unit 131 is set in a partial storage area of the storage unit 13. When an error occurs in communication between the transmission/reception unit 15 and the sensor 105, the temporary storage unit 131 temporarily stores time series data of biometric information that has not yet been used to calculate the intermediate representative value at that time.

Based on the number of intermediate representative values already calculated, the error processing unit 114 monitors the number of time series data of biometric information used by the first representative value acquisition unit 110 to calculate the intermediate representative value. More specifically, when an error occurs in communication between the transmission/reception unit 15 and the sensor 105, the error processing unit 114 checks whether there is any time series data of biometric information that has not yet been used to calculate the intermediate representative value at that time (hereinafter, this will be appropriately referred to as pre-error time series data). When pre-error time series data exists, the error processing unit 114 stores the pre-error time series data in the temporary storage unit 131. The pre-error time series data is time series data transmitted before the error occurred.

Fig. 14 is a diagram showing an example of a data string of time-series data of biological information transmitted from a sensor. In Fig. 14, each of the time-series data D1 to D15 of biological information indicates the time-series data of biological information transmitted from the sensor 105 in sequence over time. In the example of Fig. 4, one intermediate representative value calculation range is set to 60 seconds (t1 (30 seconds) to t2 (90 seconds)). In Fig. 14, one intermediate representative value calculation range is set to five pieces of time-series data of biological information (for example, time-series data D1 to D5). In other words, each of the time-series data D1 to D15 in Fig. 14 corresponds to 60/5=12 seconds of time-series data of biological information.
As shown in FIG. 14, if the time series data D6 to D9 of the four pieces of biological information have not yet been used to calculate the intermediate representative value at the time a communication error occurs, the error processing unit 114 stores the time series data D6 to D9 of the four pieces of biological information in the temporary storage unit 131 as pre-error time series data.

When communication between the transmitting/receiving unit 15 and the sensor 105 is restored from an error and communication between the transmitting/receiving unit 15 and the sensor 105 is reconnected, the error processing unit 114 calls up the pre-error time series data (time series data D6 to D9 in the example of FIG. 14) stored in the temporary storage unit 131. The error processing unit 114 calculates an intermediate representative value using the called pre-error time series data and data transmitted from the sensor 105 after the error occurred (hereinafter, this is appropriately referred to as post-error time series data).

More specifically, as shown in FIG. 14, the error processing unit 114 calculates an intermediate representative value using the time series data D6 to D9 of the four pieces of biological information called up from the temporary storage unit 131 and the time series data D10 of the biological information transmitted from the sensor 105 after the error occurred.

[Biometric information analysis system]
Next, a biological information analysis system that specifically configures the biological information analysis device 1 according to the present invention will be described with reference to FIG.
15, the bioinformation analysis system includes a sensor terminal 200, a relay terminal 300B, and an external terminal 400. The sensor terminal 200 and the external terminal 400 have the same configurations as the sensor terminal 200 and the external terminal 400 described in the first embodiment.

[Function block of relay terminal]
The relay terminal 300B includes a data receiving unit 301 , a data storage unit 302B, a time acquiring unit 303 , a control unit 304B, and a data transmitting unit 307 .

The data storage unit 302B has a temporary storage unit 3021. The temporary storage unit 3021 corresponds to the temporary storage unit 131 (Figure 13).

The control unit 304B includes a first representative value acquisition unit 305B, a second representative value acquisition unit 306, and an error processing unit 308. The error processing unit 308 corresponds to the error processing unit 114 described in FIG. 13.

[Operation sequence of the biological information analysis system]
Next, the operation of the bioinformation analysis device 1B according to this embodiment when the functions are realized by a bioinformation analysis system including the sensor terminal 200, the relay terminal 300B, and the external terminal 400 described in Fig. 15 will be described with reference to the sequence diagram shown in Fig. 16. Note that the functional blocks of the sensor terminal 200, the relay terminal 300B, and the external terminal 400 have the same configuration as that described in Fig. 15.

First, the sensor terminal 200 is worn by the user 500, and measures, for example, the heart rate as biometric information of the user 500 (step S300). More specifically, the sensor terminal 200 detects the cardiac potential of the user 500 with a heart rate meter (sensor 201). The sensor data acquisition unit 202 acquires the cardiac potential from the sensor 201, and calculates the heart rate from the electrocardiogram waveform based on the cardiac potential. The acquired cardiac potential and heart rate are stored in the data storage unit 203.

Next, the sensor terminal 200 transmits the measured heart rate to the relay terminal 300B via the communication network NW (step S301). More specifically, the data transmission unit 204 reads out the time series data of the heart rate from the data storage unit 203 and transmits it to the relay terminal 300B via the communication network NW.

When the relay terminal 300B receives time series data of the user's 500 heart rate from the sensor terminal 200, it stores the received time series data in the data storage unit 302 (step S302).

The error processing unit 308 monitors whether or not an error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301 (step S303). If no error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301, the control unit 304B proceeds to step S308, and the first representative value acquisition unit 305 calculates the intermediate representative value _Ai .
When the error processing unit 308 detects in step S303 that an error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301, it checks whether there is pre-error time series data that has not yet been used to calculate the intermediate representative value at that time (step S304). If there is no pre-error time series data, the error processing unit 308 waits to perform processing until the communication error is resolved. If there is pre-error time series data, the error processing unit 308 stores the pre-error time series data in the temporary storage unit 3021 (step S305).

The error processing unit 308 monitors whether the communication between the sensor terminal 200 and the data receiving unit 301 has recovered from the error (step S306). When the communication between the sensor terminal 200 and the data receiving unit 301 has recovered from the error, the error processing unit 308 passes the time series data to the first representative value acquisition unit 305 (step S307). To do this, the error processing unit 308 calls up the pre-error time series data from the temporary storage unit 3021. The error processing unit 308 calls up the time series data of the biological information transmitted from the sensor terminal 200 after the error occurred (post-error time series data) from the data storage unit 302. The error processing unit 308 passes the called pre-error time series data and post-error time series data to the first representative value acquisition unit 305.

The first representative value acquisition unit 305 uses the pre-error time series data and the post-error time series data to calculate an intermediate representative value _Ai for every 60 seconds according to the above-mentioned formula (2) (step S308).

Then, based on the calculated intermediate representative value, the second representative value acquisition unit 306 calculates a final representative value (step S309). Next, the calculated final representative value is transmitted from the relay terminal 300B to the external terminal 400 (step S310).

The external terminal 400 then receives the final representative value. The external terminal 400 performs a presentation process based on the final representative value (step S311), displays the final representative value on a display device, and generates and outputs support information for the user 500.

[Advantages of the Third Embodiment]
As described above, according to the bioinformation analyzer 1B of the third embodiment, the intermediate representative value is acquired using the pre-error time series data transmitted before the error occurs and stored in the temporary storage unit 3021, and the post-error time series data transmitted from the sensor terminal 200 after the error occurs. This allows all the time series data of the biological information arriving at the relay terminal 300B to be subject to the calculation process of the intermediate representative value, and it is possible to provide the user with support information that has been precisely downsampled without any timestamp deviation. As a result, even if a failure occurs in communication between the sensor terminal 200 and the data receiving unit 301, it is possible to prevent a decrease in accuracy and loss of data.

[Fourth embodiment]
Next, a fourth embodiment of the present invention will be described. In the following description, the same components as those in the first to third embodiments are given the same reference numerals, and the description thereof will be omitted.

In the fourth embodiment, the calculation process of the intermediate representative value is different from the first to third embodiments. In the fourth embodiment, the calculation process of the intermediate representative value is performed assuming a case where a communication failure (error) occurs between the sensor terminal 200 and the relay terminal 300C. The configuration of the fourth embodiment will be described below.
17, the bioinformation analyzer 1C includes a control unit 11C, a temporary storage unit 131, and a log storage unit 132. The control unit 11C includes a first representative value acquisition unit 110, a second representative value acquisition unit 111, an error processing unit 114, and a usability determination unit 115C. Other functional configurations of the bioinformation analyzer 1C are similar to those of the third embodiment.

The log storage unit 132 is set in a part of the storage area of the storage unit 13 together with the temporary storage unit 131. The log storage unit 132 records log information including the contents and time of the procedure for receiving time series data from the sensor 105 in the transmission/reception unit 15. The log storage unit 132 stores the error contents when an error occurs in communication with the sensor 105 as log information together with time information. The error contents include, for example, a BLE (Bluetooth Low Energy) communication disconnection, packet loss, demodulation failure, etc. When a BLE communication disconnection occurs, some relay terminals 300C perform automatic BLE reconnection, so the log of this automatic reconnection request is also stored as log information. In addition, when a normal communication termination operation is performed, the record of the procedure is stored as log information.

The usability determination unit 115C determines whether or not to use the pre-error time series data stored in the temporary storage unit 131 to obtain an intermediate representative value based on the log information stored in the log storage unit 132. More specifically, the usability determination unit 115C refers to the log information at the time of communication interruption stored in the log storage unit 132. If the content of the referred log information is, for example, related to a communication failure or automatic reconnection, the usability determination unit 115C determines that the pre-error time series data can be used to obtain an intermediate representative value. If the content of the referred log information is similar to an operation for normally terminating communication, the usability determination unit 115C determines that the pre-error time series data cannot be used to obtain an intermediate representative value.

Specifically, for example, as shown in FIG. 18, if the time series data D6 to D9 of the four pieces of biometric information have not yet been used to calculate the intermediate representative value at the time a communication error occurs, the usability determination unit 115C stores the time series data D6 to D9 of the four pieces of biometric information in the temporary storage unit 131 as pre-error time series data.
If the content of the log information recorded when an error occurs is related to a communication failure or automatic reconnection, the usability determination unit 115C determines that the four pieces of time-series data D6 to D9 of biometric information stored in the temporary storage unit 131 are usable. If the content of the log information is related to a normal communication termination operation, the usability determination unit 115C determines that the four pieces of time-series data D6 to D9 of biometric information stored in the temporary storage unit 131 are unusable.

When the communication between the transmission/reception unit 15 and the sensor 105 is restored from the error and the communication between the transmission/reception unit 15 and the sensor 105 is reconnected, the error processing unit 114 refers to the judgment result of the usability judgment unit 115C. When the error processing unit 114 judges that the pre-error time series data stored in the temporary storage unit 131 is usable, in the specific example of FIG. 18, it calls the time series data D6 to D9. The first representative value acquisition unit 110 calculates an intermediate representative value using the called pre-error time series data and the post-error time series data (time series data D10 in the specific example of FIG. 18) transmitted from the sensor 105 after the error occurred. When the error processing unit 114 judges that the pre-error time series data stored in the temporary storage unit 131 is unusable, in the specific example of FIG. 18, it calculates an intermediate representative value using only the post-error time series data (time series data D10 to D14 in the specific example of FIG. 18) transmitted from the sensor 105 after the error occurred.

[Biometric information analysis system]
Next, a biological information analysis system that specifically configures the biological information analysis device 1 according to the present invention will be described with reference to FIG.
19, the bioinformation analysis system includes a sensor terminal 200, a relay terminal 300C, and an external terminal 400. The sensor terminal 200 and the external terminal 400 have the same configurations as the sensor terminal 200 and the external terminal 400 described in the first embodiment.

[Function block of relay terminal]
The relay terminal 300C includes a data receiving unit 301, a data storage unit 302C, a time acquiring unit 303, a control unit 304C, and a data transmitting unit 307.

The data storage unit 302C has a temporary storage unit 3021 and a log storage unit 3022. The log storage unit 3022 corresponds to the log storage unit 132 (Figure 17).

The control unit 304C includes a first representative value acquisition unit 305C, a second representative value acquisition unit 306, an error processing unit 308, and a usability determination unit 309. The usability determination unit 309 corresponds to the usability determination unit 115C described in FIG. 17.

[Operation sequence of the biological information analysis system]
Next, the operation of the bioinformation analysis device 1C according to this embodiment when the functions are realized by a bioinformation analysis system including the sensor terminal 200, the relay terminal 300C, and the external terminal 400 described in Fig. 19 will be described with reference to the sequence diagram shown in Fig. 20. Note that the functional blocks of the sensor terminal 200, the relay terminal 300C, and the external terminal 400 have the same configuration as that described in Fig. 19.

First, the sensor terminal 200 is worn by the user 500, and measures, for example, the heart rate as biometric information of the user 500 (step S400). More specifically, the sensor terminal 200 detects the cardiac potential of the user 500 with a heart rate meter (sensor 201). The sensor data acquisition unit 202 acquires the cardiac potential from the sensor 201, and calculates the heart rate from an electrocardiogram waveform based on the cardiac potential. The acquired cardiac potential and heart rate are stored in the data storage unit 203.

Next, the sensor terminal 200 transmits the measured heart rate to the relay terminal 300C via the communication network NW (step S401). More specifically, the data transmission unit 204 reads out the time series data of the heart rate from the data storage unit 203 and transmits it to the relay terminal 300C via the communication network NW.

When the relay terminal 300C receives the time series data of the heart rate of the user 500 from the sensor terminal 200, the relay terminal 300C stores the received time series data in the data storage unit 302 (step S402).
When the log storage unit 132 receives the time series data of the heart rate from the sensor terminal 200, it records log information including the details and time of the procedure performed in receiving the time series data from the sensor terminal 200 at the data receiving unit 301 (step S403).

The error processing unit 308 monitors whether or not an error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301 (step S404). If no error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301, the control unit 304C proceeds to step S410, and the first representative value acquisition unit 305 calculates the intermediate representative value _Ai .

If it is detected in step S404 that an error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301, the error processing unit 308 checks whether there is pre-error time series data that has not yet been used to calculate the intermediate representative value (step S405). If there is no pre-error time series data, the error processing unit 308 waits to perform processing until the communication error is resolved. If there is pre-error time series data, the error processing unit 308 stores the pre-error time series data in the temporary storage unit 3021 (step S406).

The error processing unit 308 monitors whether the communication between the sensor terminal 200 and the data receiving unit 301 has been restored from the error (step S407). When the communication between the sensor terminal 200 and the data receiving unit 301 has been restored from the error, the usability determination unit 309 determines whether the pre-error time series data can be used (step S408). Based on the log information, the usability determination unit 309 determines whether the pre-error time series data stored in the temporary storage unit 3021 can be used to obtain the intermediate representative value. More specifically, the usability determination unit 309 refers to the log information at the time of communication interruption stored in the log storage unit 3022. If the content of the referred log information is, for example, related to communication failure or automatic reconnection, the usability determination unit 309 determines that the pre-error time series data can be used to obtain the intermediate representative value. If the content of the referred log information is similar to a normal communication termination operation, the usability determination unit 309 determines that the pre-error time series data cannot be used to obtain the intermediate representative value.

The error processing unit 308 passes the time series data to the first representative value acquisition unit 305 based on the determination result by the usability determination unit 309 (step S409). If the usability determination unit 309 determines that the pre-error time series data is usable for acquiring an intermediate representative value, the error processing unit 308 calls up the pre-error time series data from the temporary storage unit 3021. The error processing unit 308 calls up the time series data of the biological information transmitted from the sensor terminal 200 after the error occurred (post-error time series data) from the data storage unit 302. The error processing unit 308 passes the called pre-error time series data and post-error time series data to the first representative value acquisition unit 305.
Furthermore, if the usability determination unit 309 determines that the pre-error time-series data cannot be used to acquire the intermediate representative value, the error processing unit 308 calls the time-series data of the biological information transmitted from the sensor terminal 200 after the error occurred (post-error time-series data) from the data storage unit 302. The error processing unit 308 passes the post-error time-series data to the first representative value acquisition unit 305.

In the first representative value acquisition unit 305, when it is determined that the pre-error time series data can be used to acquire the intermediate representative value, the pre-error time series data and the post-error time series data are used to calculate the intermediate representative value A _i (step S410). In the first representative value acquisition unit 305, when it is determined that the pre-error time series data cannot be used to acquire the intermediate representative value, the post-error time series data alone is used to calculate the intermediate representative value A _i

Then, based on the calculated intermediate representative value, the second representative value acquisition unit 306 calculates a final representative value (step S411). Next, the calculated final representative value is transmitted from the relay terminal 300C to the external terminal 400 (step S412).

The external terminal 400 then receives the final representative value. The external terminal 400 performs a presentation process based on the final representative value (step S413), displays the final representative value on a display device, and generates and outputs support information for the user 500.

[Advantages of the Fourth Embodiment]
As described above, according to the biometric information analysis device 1C of the fourth embodiment, the intermediate representative value is obtained using the pre-error time series data transmitted before the error occurs and stored in the temporary storage unit 3021, and the post-error time series data transmitted from the sensor terminal 200 after the error occurs. In addition, based on the log information, the availability of the pre-error time series data is determined according to the situation when the communication error occurs. As a result, when the user stops continuing the communication, the calculation process is stopped, and otherwise, the time series data of the biometric information arriving at the relay terminal 300C can be used for the calculation process of the intermediate representative value without omission. As a result, even if a failure occurs in the communication between the sensor terminal 200 and the data receiving unit 301, it is possible to prevent a decrease in accuracy and a loss of data.
[Fifth embodiment]
Next, a fifth embodiment of the present invention will be described. In the following description, the same components as those in the first to fourth embodiments are given the same reference numerals, and the description thereof will be omitted.

In the fifth embodiment, the calculation process of the intermediate representative value is different from the first to fourth embodiments. In the fifth embodiment, the calculation process of the intermediate representative value is performed assuming a case where a communication failure (error) occurs between the sensor terminal 200 and the relay terminal 300D. The configuration of the fifth embodiment will be described below.
21, the biometric information analyzer 1D includes a control unit 11D and a temporary storage unit 131. The control unit 11D includes a first representative value acquisition unit 110, a second representative value acquisition unit 111, an error processing unit 114, a usability determination unit 115D, and a stamp time monitoring unit 116. Other functional configurations of the biometric information analyzer 1D are similar to those of the third embodiment.

In this embodiment, the sensor 105 transmits information indicating the time when the time series data was acquired in association with the time series data. In this embodiment, information indicating the time when the time series data transmitted by the sensor 105 arrived at the transmission/reception unit 15 may be associated with the time series data.

The stamp time monitoring unit 116 monitors the time when the time series data is acquired by the sensor 105, or the time when the time series data arrives at the transmission/reception unit 15. When an error occurs in communication with the sensor 105, the stamp time monitoring unit 116 determines whether the time interval between the time information of the pre-error time series data and the time information of the post-error time series data exceeds a predetermined threshold value.

The usability determination unit 115D determines whether or not to use the pre-error time series data stored in the temporary storage unit 131 to obtain an intermediate representative value based on the result of monitoring by the stamp time monitoring unit 116. More specifically, if the time interval between the time information of the pre-error time series data and the time information of the post-error time series data does not exceed a predetermined threshold, the usability determination unit 115D determines that the pre-error time series data can be used to obtain an intermediate representative value. If the time interval between the time information of the pre-error time series data and the time information of the post-error time series data exceeds a predetermined threshold, the usability determination unit 115D determines that the pre-error time series data cannot be used to obtain an intermediate representative value.

Specifically, for example, as shown in FIG. 22, if the time series data D6 to D9 of the four pieces of biometric information have not yet been used to calculate the intermediate representative value at the time a communication error occurs, the usability determination unit 115D stores the time series data D6 to D9 of the four pieces of biometric information in the temporary storage unit 131 as pre-error time series data.
The usability determination unit 115D determines that the pre-error time series data is usable if the time interval between the time information of the pre-error time series data and the time information of the post-error time series data before and after the occurrence of an error does not exceed a predetermined threshold. If the time interval between the time information of the pre-error time series data and the time information of the post-error time series data exceeds a predetermined threshold, the usability determination unit 115D determines that the time series data D6 to D9 of the four pieces of biometric information stored in the temporary storage unit 131 are unusable.

When the communication between the transmission/reception unit 15 and the sensor 105 is restored from the error and the communication between the transmission/reception unit 15 and the sensor 105 is reconnected, the error processing unit 114 refers to the judgment result of the usability judgment unit 115D. When the error processing unit 114 judges that the pre-error time series data stored in the temporary storage unit 131 is usable, in the specific example of FIG. 22, it calls the time series data D6 to D9. The first representative value acquisition unit 110 calculates an intermediate representative value using the called pre-error time series data and the post-error time series data (time series data D10 in the specific example of FIG. 22) transmitted from the sensor 105 after the error occurred. When the error processing unit 114 judges that the pre-error time series data stored in the temporary storage unit 131 is unusable, in the specific example of FIG. 22, it calculates an intermediate representative value using only the post-error time series data (time series data D10 to D14 in the specific example of FIG. 22) transmitted from the sensor 105 after the error occurred.

[Biometric information analysis system]
Next, a biological information analysis system that specifically configures the biological information analysis device 1 according to the present invention will be described with reference to FIG.
23, the bioinformation analysis system includes a sensor terminal 200, a relay terminal 300D, and an external terminal 400. The sensor terminal 200 and the external terminal 400 have the same configurations as the sensor terminal 200 and the external terminal 400 described in the first embodiment.

[Function block of relay terminal]
The relay terminal 300D includes a data receiving unit 301, a data storage unit 302D, a time acquiring unit 303, a control unit 304D, and a data transmitting unit 307.

The control unit 304D includes a first representative value acquisition unit 305D, a second representative value acquisition unit 306, an error processing unit 308, a usability determination unit 309, and a stump time monitoring unit 310. The stump time monitoring unit 310 corresponds to the stump time monitoring unit 116 described in FIG. 21.

[Operation sequence of the biological information analysis system]
Next, the operation of the bioinformation analysis device 1D according to this embodiment when the functions are realized by a bioinformation analysis system including the sensor terminal 200, the relay terminal 300D, and the external terminal 400 described in Fig. 23 will be described with reference to the sequence diagram shown in Fig. 24. Note that the functional blocks of the sensor terminal 200, the relay terminal 300D, and the external terminal 400 have the same configuration as that described in Fig. 23.

First, the sensor terminal 200 is worn by the user 500, and measures, for example, the heart rate as biometric information of the user 500 (step S500). More specifically, the sensor terminal 200 detects the cardiac potential of the user 500 with a heart rate monitor (sensor 201). The sensor data acquisition unit 202 acquires the cardiac potential from the sensor 201, and calculates the heart rate from an electrocardiogram waveform based on the cardiac potential. The acquired cardiac potential and heart rate are stored in the data storage unit 203. The sensor data acquisition unit 202 stores time information when the cardiac potential was acquired by the sensor 201 in association with the cardiac potential.

Next, the sensor terminal 200 transmits the measured heart rate to the relay terminal 300D via the communication network NW (step S501). More specifically, the data transmission unit 204 reads out the time series data of the heart rate from the data storage unit 203 and transmits it to the relay terminal 300D via the communication network NW.

When the relay terminal 300D receives the time series data of the heart rate of the user 500 from the sensor terminal 200, the relay terminal 300D stores the received time series data in the data storage unit 302 (step S502).
When the stamped time monitoring unit 116 receives the time series data of the heart rate from the sensor terminal 200, it refers to the time information associated with the time series data (step S503).

The error processing unit 308 monitors whether or not an error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301 (step S503). If no error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301, the control unit 304D proceeds to step S510, and the first representative value acquisition unit 305 calculates the intermediate representative value _Ai .

If it is detected in step S503 that an error has occurred in the communication between the sensor terminal 200 and the data receiving unit 301, the error processing unit 308 checks whether there is pre-error time series data that has not yet been used to calculate the intermediate representative value (step S504). If there is no pre-error time series data, the error processing unit 308 waits to perform processing until the communication error is resolved. If there is pre-error time series data, the error processing unit 308 stores the pre-error time series data in the temporary storage unit 3021 (step S505).

The error processing unit 308 monitors whether the communication between the sensor terminal 200 and the data receiving unit 301 has recovered from the error (step S506). When the communication between the sensor terminal 200 and the data receiving unit 301 has recovered from the error, the stamp time monitoring unit 310 monitors the time information of the time series information that arrived before and after the error (step S507). The stamp time monitoring unit 310 determines whether the time interval between the time information of the pre-error time series data and the time information of the post-error time series data exceeds a predetermined threshold.

Next, the usability determination unit 309 determines whether or not the pre-error time series data stored in the temporary storage unit 3021 is to be used to obtain an intermediate representative value based on the result of the monitoring by the time stamp monitoring unit 310 (step S50). The usability determination unit 115D determines that the pre-error time series data can be used to obtain an intermediate representative value if the time interval between the time information of the pre-error time series data and the time information of the post-error time series data does not exceed a predetermined threshold. The usability determination unit 309 determines that the pre-error time series data cannot be used to obtain an intermediate representative value if the time interval between the time information of the pre-error time series data and the time information of the post-error time series data exceeds a predetermined threshold.

The error processing unit 308 passes the time series data to the first representative value acquisition unit 305 based on the determination result by the usability determination unit 309 (step S509). If the usability determination unit 309 determines that the pre-error time series data is usable for acquiring an intermediate representative value, the error processing unit 308 calls up the pre-error time series data from the temporary storage unit 3021. The error processing unit 308 calls up the time series data of the biological information transmitted from the sensor terminal 200 after the error occurred (post-error time series data) from the data storage unit 302. The error processing unit 308 passes the called pre-error time series data and post-error time series data to the first representative value acquisition unit 305.
Furthermore, if the usability determination unit 309 determines that the pre-error time-series data cannot be used to acquire the intermediate representative value, the error processing unit 308 calls the time-series data of the biological information transmitted from the sensor terminal 200 after the error occurred (post-error time-series data) from the data storage unit 302. The error processing unit 308 passes the post-error time-series data to the first representative value acquisition unit 305.

In the first representative value acquisition unit 305, when it is determined that the pre-error time series data can be used to acquire the intermediate representative value, the pre-error time series data and the post-error time series data are used to calculate the intermediate representative value A _i (step S510). In the first representative value acquisition unit 305, when it is determined that the pre-error time series data cannot be used to acquire the intermediate representative value, the post-error time series data alone is used to calculate the intermediate representative value A _i

Then, based on the calculated intermediate representative value, the second representative value acquisition unit 306 calculates a final representative value (step S511). Next, the calculated final representative value is transmitted from the relay terminal 300D to the external terminal 400 (step S512).

The external terminal 400 then receives the final representative value. The external terminal 400 performs a presentation process based on the final representative value (step S513), displays the final representative value on a display device, and generates and outputs support information for the user 500.

[Advantages of the Fifth Embodiment]
As described above, according to the biometric information analysis device 1D of the fifth embodiment, the intermediate representative value is obtained using the pre-error time series data transmitted before the error occurs and stored in the temporary storage unit 3021, and the post-error time series data transmitted from the sensor terminal 200 after the error occurs. In addition, the availability of the pre-error time series data is determined based on the time interval between the time series data before and after the error. As a result, when the downtime due to the error is long, the calculation process using the pre-error time series data is stopped, and otherwise, the time series data of the biometric information arriving at the relay terminal 300D can be used for the calculation process of the intermediate representative value without omission. As a result, even if a failure occurs in the communication between the sensor terminal 200 and the data receiving unit 301, it is possible to prevent a decrease in accuracy and a loss of data.

[Modifications of the Fourth and Fifth Embodiments]
The biological information analysis system according to this modification is a modification of the fourth and fifth embodiments. According to this modification, as shown in Fig. 25, a biological information analysis device 1E in this embodiment includes the log storage unit 132 described in the fourth embodiment and the stamp time monitoring unit 116 described in the fifth embodiment.
In this configuration, even if the contents of the log information are related to communication failure or automatic reconnection, if the time interval of the time information of the time series data exceeds a certain threshold, calculation processing using the pre-error time series data is not performed. As a result, for example, if it is highly likely that the user's situation has changed due to the passage of a long time, calculation processing of the representative value can be performed only with the post-error time series data without using the pre-error time series data. This makes it possible to properly grasp whether the user's intended operation was performed from the communication situation, and at the same time, to calculate the representative value according to the user's situation from the time stamp interval, and to provide a more reliable downsampled average value.

Sixth embodiment
Next, a sixth embodiment of the present invention will be described. In the following description, the same components as those in the first to fifth embodiments are given the same reference numerals, and the description thereof will be omitted.

In the first to fifth embodiments, an example was given in which an average value was calculated as the intermediate representative value and the final representative value of the time-series data of the biometric information. In contrast, in the sixth embodiment, a ratio is calculated as the statistical representative value of the time-series data of the biometric information, instead of an average value.

The configuration of the bioinformation analysis device 1 according to this embodiment is similar to the configuration of the bioinformation analysis device 1 shown in Fig. 1. The configuration of the bioinformation analysis system according to this embodiment is also similar to the configuration shown in Fig. 6. Below, the configuration different from the first to fifth embodiments will be mainly described.

As shown in the first embodiment, the average of vital signs such as heart rate, body temperature, and blood pressure can be calculated over time. However, it is not necessarily appropriate to calculate the average in this way for other vital signs. For example, there is the case where the user's state is estimated by a sensor. If the state of the user lying face down (sleeping) is 0 and the state of being awake is 1, and the state of the user is always classified as one of these two values, then the value of 0.5 obtained by taking the average of these values is meaningless.

Information that can take intermediate values, such as heart rate, is called a quantitative variable, while information that does not allow intermediate values and represents a state, such as posture, is called a qualitative variable. When analyzing such qualitative variables in the bioinformation analysis device 1, it is desirable to use a ratio that represents the frequency of their occurrence.

For example, let the lying down (sleeping) state be 0, the awake state be 1, and the walking state be 2, and suppose that the intermediate representative value Ai is calculated every 60 seconds with a sampling rate of 1 second. In this case, if the lying down period includes 30 seconds, the awake period includes 20 seconds, and the walking period includes 10 seconds, then let these numbers be N0,i, N1,i, and N2,i, and they can be expressed by the following equation (3).

In addition, in the case of the above formula (3), for example, if the final representative value Bi is the most frequent value, the final representative value Bi is calculated using the following formula (4).

Note that in the above formula (4), the output of the final representative value Bi = 1 is just one example, and indicates, for example, that the awake state was the most frequent state. However, the configuration in which the most frequent value is taken as the final representative value Bi is just one example, and other determination methods may be used. For example, of the three states described above, lying down, awake, and walking, walking is considered to be the least likely state to occur because it requires the most physical strength. Therefore, for example, if the user has been walking for six seconds or more, the walking state may be selected as a priority.

In this case, the intermediate representative value Ai is expressed by the following equation (5).

When using the above formula (5) to output the state in which the user is walking as the intermediate representative value Ai, for example, if the user does not walk for more than 6 seconds, the state (0 or 1) of either the lying down period N0,i or the awake period N1,i, whichever is longer, is determined by majority vote and is set as the intermediate representative value Ai.

When calculating the final representative value Bi based on the intermediate representative value Ai calculated using the above formula (5), the calculation to determine the final representative value Bi can be performed by determining that if there is at least one intermediate representative value Ai indicating that the user has been walking among multiple consecutive intermediate representative values Ai, this is regarded as walking.

However, since the numerical value indicating the state of whether or not the user has walked changes very rapidly compared to the increase and decrease of values such as heart rate and blood pressure, the intermediate representative value Ai may be directly set equal to the final representative value Bi. In particular, when multiple sensors are used in combination, it is more intuitive for the user to calculate the final representative value Bi for quantitative variables by performing a calculation based on the intermediate representative value Ai, and it is more intuitive for the user such as the user to use the intermediate representative value Ai as the final representative value Bi for qualitative variables.

[Operation sequence of the biological information analysis system]
Next, the operation of the bioinformation analysis device 1 according to this embodiment when each function is realized by a bioinformation analysis system including the sensor terminal 200, relay terminal 300, and external terminal 400 described in Fig. 6 will be described with reference to the sequence diagram shown in Fig. 17. Note that each functional block of the sensor terminal 200, relay terminal 300, and external terminal 400 has the same configuration as described in Fig. 6.

First, the sensor terminal 200 is attached to the user 500, and measures, for example, posture and walking as biometric information of the user 500 (step S700). More specifically, the sensor terminal 200 detects acceleration data of the user 500 using a three-axis acceleration sensor (sensor 201). The sensor data acquisition unit 202 acquires the acceleration data from the sensor 201, and measures the state of the user 500 lying down, awake, or walking from the inclination and body movement based on the acceleration data. Time series data of the biometric information indicating the measured posture and walking state of the user is stored in the data storage unit 203.

Next, the sensor terminal 200 transmits the measured biometric information indicating the user's posture and gait to the relay terminal 300 via the communication network NW (step S701). More specifically, the data transmission unit 204 reads out time-series data of the biometric information indicating the user's state from the data storage unit 203 and transmits it to the relay terminal 300 via the communication network NW.

When the relay terminal 300 receives the time series data of the biometric information indicating the state of the user 500 from the sensor terminal 200, the first representative value acquisition unit 305 calculates an intermediate representative value in the time series data of the state of the user 500 for a set period, for example, every 60 seconds (step S702). More specifically, the first representative value acquisition unit 305 calculates, for example, using the above-mentioned formula (4), the proportion of the period during which the user 500 was lying down, awake, and walking for every 60 seconds as the intermediate representative value. The calculated intermediate representative value is stored in the data storage unit 302.

Thereafter, the second representative value acquisition unit 306 calculates a final representative value based on the calculated intermediate representative value (step S703). More specifically, the second representative value acquisition unit 306 may calculate the final representative value with the highest frequency using the above-mentioned formula (5). Next, the calculated final representative value is transmitted from the relay terminal 300 to the external terminal 400 (step S704).

The external terminal 400 then receives the final representative value. The external terminal 400 performs a presentation process based on the final representative value (step S705), displays the final representative value on a display device, and generates and outputs support information for the user 500.

As described above, according to the sixth embodiment of the bioinformation analysis device 1, by using the percentage of any period as an intermediate representative value of the bioinformation, it can also be applied to sensors that measure bioinformation corresponding to qualitative variables.

The above describes embodiments of the biometric information analysis system, non-transitory storage medium, and biometric information analysis method of the present invention, but the present invention is not limited to the described embodiments, and various modifications that may be envisioned by a person skilled in the art can be made within the scope of the invention described in the claims.

In the embodiment described above, the biometric information measured by the sensor data acquisition unit 10 is described as heart rate, acceleration, posture, and walking, but the biometric information is not limited to these and may be, for example, pulse wave, blood pressure, bioimpedance, myoelectric potential, respiration, movement speed, angular velocity, air pressure, light, temperature, humidity, etc.

Technology is provided that makes it possible to prevent degradation of data accuracy and loss of data even if a failure occurs in data communication.

1, 1A, 1B, 1C, 1D...biometric information analysis device, 11, 11A, 11B, 11C, 11D...control unit, 13...storage unit, 105...sensor, 109...display device, 110...first representative value acquisition unit, 111...second representative value acquisition unit, 115C, 115D...usability determination unit, 116...stamp time monitoring unit, 131...temporary storage unit, 132...log storage unit, 200...sensor terminal, 201...sensor, 300, 30 0B, 300C, 300D... relay terminal, 301... data receiving unit, 304, 304B, 304C, 304D... control unit, 305, 305B, 305C, 305D... first representative value acquisition unit, 306... second representative value acquisition unit, 309... usability determination unit, 310... time stamp monitoring unit, 400... external terminal, 401... data receiving unit, 3021... temporary storage unit, 3022... log storage unit, D1 to D15... time series data

Claims (7)

a data receiving unit that receives time-series data of the biological information from a sensor terminal having a biological sensor that acquires the biological information;
A storage unit that stores the received time series data;
a first representative value acquisition unit that acquires a first representative value based on data for a predetermined period of the received time series data;
a second representative value acquisition unit that acquires a second representative value based on a plurality of the first representative values that are continuous on a time axis,
when an error occurs in communication between the data receiving unit and the sensor terminal, if a predetermined condition is satisfied, the first representative value acquisition unit acquires the first representative value using pre-error time series data transmitted before the error occurs and stored in the storage unit, and post-error time series data transmitted from the sensor terminal after the error occurs ;
a usability determination unit that determines whether or not the pre-error time-series data is used to obtain the first representative value,
The first representative value acquisition unit acquires the first representative value using the pre-error time-series data when the usability determination unit determines that the pre-error time-series data is to be used to acquire the first representative value. The storage unit further includes a temporary storage unit that temporarily stores the pre-error time series data,
The bioinformation analysis system of claim 1, wherein when an error occurs in communication between the data receiving unit and the sensor terminal, the first representative value acquisition unit acquires the first representative value using pre-error time series data stored in the temporary storage unit and post-error time series data transmitted from the sensor terminal after the error occurs. a log storage unit configured to record log information including a procedure and a procedure time when the data receiving unit receives the time-series data from the sensor terminal;
The biological information analyzing system according to claim 1 , wherein the usability determining unit determines whether or not the pre-error time-series data is to be used to obtain the first representative value, based on the log information stored in the log storage unit. a time stamp monitoring unit that monitors a time when the time series data is acquired by the sensor terminal or a time when the time series data arrives at the data receiving unit;
The biometric information analysis system according to claim 1 , wherein the usability determination unit determines whether or not to use the pre-error time series data to obtain the first representative value based on a result of the time monitoring by the time stamp monitoring unit. 5. The bioinformation analysis system according to claim 1 , wherein the bioinformation includes at least one of an electrocardiogram waveform, a heart rate, a pulse wave, a blood pressure, a bioimpedance, a myoelectric potential, a respiration, a moving speed, an acceleration, an angular velocity, an atmospheric pressure, a light, and a temperature and humidity. A non-transitory storage medium storing a program for causing a computer to function as the bioinformation analysis system according to any one of claims 1 to 5 . a data receiving step in which the computer receives time-series data of the biological information from a sensor terminal having a biological sensor for acquiring the biological information via a data receiving unit ;
A recording step in which the computer records the received time series data in a storage unit ;
a first representative value acquisition step of acquiring a first representative value based on data for a predetermined period of the received time-series data;
a second representative value acquisition step of acquiring a second representative value based on the plurality of first representative values that are successive on a time axis ,
In the first representative value acquisition step, when an error occurs in communication between the data receiving unit and the sensor terminal, if a predetermined condition is satisfied, the computer acquires the first representative value using pre-error time series data transmitted before the error occurs and stored in the storage unit, and post-error time series data transmitted from the sensor terminal after the error occurs ;
The method further includes a use/non-use determination step of determining whether or not the pre-error time-series data is used to obtain the first representative value,
A biological information analysis method, in which in the first representative value acquisition step, if it is determined in the usability determination step that the pre-error time series data is to be used to acquire the first representative value, the first representative value is acquired using the pre-error time series data .

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